CN112561651A - Product information pushing method and related product - Google Patents

Product information pushing method and related product Download PDF

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CN112561651A
CN112561651A CN202011499114.7A CN202011499114A CN112561651A CN 112561651 A CN112561651 A CN 112561651A CN 202011499114 A CN202011499114 A CN 202011499114A CN 112561651 A CN112561651 A CN 112561651A
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陈依云
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Ping An Life Insurance Company of China Ltd
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Ping An Life Insurance Company of China Ltd
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    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0623—Item investigation
    • G06Q30/0625—Directed, with specific intent or strategy
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The embodiment of the application discloses a product information pushing method and a related product, wherein the method comprises the following steps: determining a first relevance between first user basic information and second user basic information according to the first user basic information of a first user in a first scene and the second user basic information of a second user in a second scene; integrating first user information of a first user in a first scene and second user information of a second user in a second scene according to the first relevance to obtain third user information of the first user; determining the demand score of the first user for the first product according to the third user information; and pushing the product information of the first product to the first user according to the demand score. According to the embodiment of the application, the demand score of the first user on the first product is determined according to the integrated first user information, the product information is pushed to the first user according to the demand score, the first user information is perfected, and the product pushing efficiency is improved.

Description

Product information pushing method and related product
Technical Field
The present application relates to the field of computer technologies, and in particular, to a product information pushing method and a related product.
Background
Along with the development of Chinese economy, the increase of the income of the national wealth, the gradual strengthening of the insurance consciousness of the national people, and the increasing urgency and diversification of the financial management demand and the insurance demand of residents, however, as the financial management information and the insurance information products are various and complex, and the demands of users on the financial management and the insurance are different, when the users want to recommend the financial management products and the insurance products of the suitable users, the manual inquiry mode is usually adopted, so that the manpower and material resources are greatly needed, and the efficiency is low.
Disclosure of Invention
The embodiment of the application mainly aims to provide a product information pushing method and a related product, and the problem of low recommendation efficiency when financial products and insurance products of a proper user are recommended to the user can be effectively solved.
In a first aspect, an embodiment of the present application provides a product information pushing method, which is applied to an electronic device, and the method includes:
acquiring first user basic information of a first user in a first scene and second user basic information of a second user in a second scene, wherein the user basic information refers to personal information of the user and personal information of a first contact person associated with the user in the scene;
identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information;
integrating first user information of the first user in a first scene and second user information of the second user in a second scene according to the first relevance to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information;
determining the demand score of the first user for the first product according to the third user information;
and pushing the product information of the first product to the first user according to the demand score.
Optionally, before determining the demand score of the first user for the first product according to the third user information, the method further includes: and establishing a demand scoring model of the first user for the first product demand.
Optionally, the establishing a demand scoring model of the first user for the first product demand includes:
and converting user information of a first user into a target variable by taking the user information of the first user as a predictive variable, and constructing the demand scoring model, wherein the demand scoring model is a scoring model of the first user for the first product.
Optionally, the determining a demand score of the first user for the first product according to the third user information includes: and determining the demand score of the first user on the first product according to the third user information of the first user by using a demand scoring model.
Optionally, the demand scoring model comprises a logistic regression prediction model.
Optionally, the pushing the product information of the first product to the first user according to the demand score includes: determining the process of the first user according to the demand score of the first user; and pushing the product information of the first product to the first user according to the process of the first user.
Optionally, the logistic regression prediction model is: score (y ═ 1| X) ═ β0+β1X1+β2X2+…++βnXnWhere Score (y ═ 1| X) represents the model Score for customer conversion under known label conditions, βnA label weight value, X, for the third user informationnA label for third user information.
In a second aspect, an embodiment of the present application provides a product information pushing apparatus, where the apparatus includes:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring first user basic information of a first user in a first scene and second user basic information of a second user in a second scene;
the identification unit is used for identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information;
the integration unit is used for integrating first user information of the first user in a first scene and second user information of the second user in a second scene according to the first relevance to obtain third user information of the first user;
the determining unit is used for determining the demand score of the first user for the first product according to the third user information;
and the pushing unit is used for pushing the product information of the first product to the first user according to the demand score.
Optionally, before determining the demand score of the first user for the first product according to the third user information, the determining unit 504 is further specifically configured to: and establishing a demand scoring model of the first user for the first product demand.
Optionally, in the aspect of establishing the model for scoring the demand of the first user for the first product demand, the determining unit 504 is further specifically configured to: and converting user information of a first user into a target variable by taking the user information of the first user as a predictive variable, and constructing the demand scoring model, wherein the demand scoring model is a scoring model of the first user for the first product.
Optionally, in the aspect of determining the demand score of the first user for the first product according to the third user information, the determining unit 504 is further specifically configured to: and determining the demand score of the first user on the first product according to the third user information of the first user by using a demand scoring model.
Optionally, the demand scoring model comprises a logistic regression prediction model.
Optionally, in the aspect of pushing the product information of the first product to the first user according to the demand score, the pushing unit 505 is specifically configured to: determining the process of the first user according to the demand score of the first user; and pushing the product information of the first product to the first user according to the process of the first user.
Optionally, the logistic regression prediction model is: score (y ═ 1| X) ═ β0+β1X1+β2X2+…++βnXnWhere Score (y ═ 1| X) represents the model Score for customer conversion under known label conditions, βnTag weight for third user informationValue, XnA label for third user information.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing steps in any method of the first aspect of the embodiment of the present application.
In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform part or all of the steps described in any one of the methods of the first aspect of the present application.
In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps as described in any one of the methods of the first aspect of the embodiments of the present application. The computer program product may be a software installation package.
It can be seen that, in the embodiment of the application, by acquiring the first user basic information of the first user in the first scene and the second user basic information of the second user in the second scene, the user basic information refers to the personal information of the user and the personal information of the first contact person associated with the user in the scene; identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information; integrating first user information of the first user in a first scene and second user information of the second user in a second scene according to the first relevance to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information; determining the demand score of the first user for the first product according to the third user information; and pushing the product information of the first product to the first user according to the demand score. According to the embodiment of the application, the demand score of the first user on the first product is determined according to the integrated first user information, the product information is pushed to the first user according to the demand score, the first user information is perfected, the accuracy of the first user information is improved, and the accuracy and the efficiency of pushing the product information to the first user are improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a product information pushing method according to an embodiment of the present application;
FIG. 2 is a schematic diagram illustrating a process for determining a demand score of a first user for a first product according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a product information pushing method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application;
fig. 5 is a block diagram illustrating functional units of a product information pushing apparatus according to an embodiment of the present disclosure.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The following describes embodiments of the present application in detail.
In order to solve the problem of low recommendation efficiency when recommending financial products and insurance products of a suitable user to a user, the application provides a product information pushing method, which is applied to electronic equipment, and specifically as shown in fig. 1, the method can include but is not limited to the following steps:
s101, the electronic equipment acquires first user basic information of a first user in a first scene and second user basic information of a second user in a second scene;
the user basic information refers to personal information of a user and personal information of a first contact person associated with the user in a scene.
The user basic information may be personal information including the name, gender, birthday, contact information, certificate information, and a first contact associated with the user in the scene. Wherein the certificate information includes a certificate type and a certificate number. The contact way of the user can be common contact ways such as a mobile phone number, a landline number, an account number of instant messaging, a mailbox number and the like. The personal information of the first contact associated with the user under the scene comprises: name, job number, contact address of the first contact. The contact information of the first contact comprises any one of the following: the mobile phone number, the mailbox account number, the account number of instant messaging and the like of the first contact person. The first contact may be an associate with the user corresponding to the business in the scene.
The first user and the second user may be the same user or different users. The first user is a user in a preset scene in the database. The preset scenario may be any one of an insurance product scenario and a financial scenario, for example, a life insurance scenario (life insurance product purchase scenario), a production insurance scenario (purchase scenario such as automobile insurance, travel insurance, home insurance, and accident insurance), a bank scenario (purchase scenario such as financial product purchase scenario), and a fund scenario (purchase scenario of fund product), where the preset scenario is not limited too much.
The first scenario may be any one of an insurance product scenario and a financial scenario, for example, a life insurance scenario (life insurance product purchase scenario), a production insurance scenario (purchase scenario such as automobile insurance, travel insurance, home insurance, and accident insurance), a bank scenario (purchase scenario such as financial product purchase scenario), and a fund scenario (fund product purchase scenario), and the first scenario may also be another scenario, which is not limited herein.
The second scenario may be any one of an insurance product scenario and a financial scenario, for example, a life insurance scenario (life insurance product purchase scenario), a production insurance scenario (purchase scenario such as automobile insurance, travel insurance, home insurance, and accident insurance), a bank scenario (purchase scenario such as financial product purchase scenario), and a fund scenario (purchase scenario of fund product). The second scenario may also be other scenarios, without undue limitation.
Wherein the first scene is different from the second scene.
S102, the electronic equipment identifies the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information;
the first relevance is the relevance of the first user basic information and the second user basic information which are the same user. The first association may be divided into a strong association and a weak association, the strong association representing that the first user and the second user are the same user, and the weak association representing that the first user and the second user are different users.
As shown in table 1 below, table 1 is a table of user basic information association between a first user and a second user
Figure BDA0002841925060000061
The strongly correlated corresponding condition includes any one of the following cases:
1. condition 1: the certificate types and the certificate numbers in the first user basic information and the second user basic information are consistent, the names are consistent, the sexes are consistent, the birthdays are consistent, the contact ways are consistent, and the corresponding salesman information is not limited;
2. condition 2: the certificate types and the certificate numbers in the first user basic information and the second user basic information are absent, the names are consistent, the sexes are consistent, the birthdays are consistent, the contact ways are consistent, and the corresponding salesman information is not limited;
3. condition 3: the certificate types and the certificate numbers in the first user basic information and the second user basic information are consistent, the names are not limited, the sexes are not limited, the birthdays are not limited, the contact ways are consistent, and the corresponding salesman information is not limited.
The conditions for weak correlation correspondence include the following cases:
condition 4: the certificate type and the certificate number in the first user basic information and the second user basic information are missing, the name is not limited, the gender is not limited, the birthday is not limited, the contact way is consistent and consistent, and the corresponding salesman information is consistent and consistent.
The personal information of the first contact person is information of a single salesman corresponding to the user or information of a product service manager corresponding to the user.
It needs to be further supplemented that: the other situations except the situation corresponding to the strong correlation and the weak correlation are regarded as that the first user cannot be matched with the second user, that is, the first user and the second user are not the same user, and an Identity Document (ID) needs to be newly established for the first user basic information of the first user, wherein the ID is a user number in the user basic information in a preset scene.
In one possible example, identifying first user information of a first user in a first scenario and second user information of a second user in a second scenario to obtain a first association includes: and comparing the name, the gender, the birthday, the mobile phone number, the certificate information and the corresponding salesman information of the first user in the first user information with the name, the gender, the birthday, the mobile phone number, the certificate information and the corresponding salesman information of the second user in the second user information to obtain a first relevance between the first user and the second user.
For example, if there are two users: the first user A and the second user B are from two different scenes (such as life insurance and production insurance), if the identification numbers of the first user A and the second user B are the same, the names are the same, the sexes are the same, the birthdays are the same, and the mobile phone numbers are not limited, the condition 1 in the strong correlation condition is judged to be the first correlation of the first user A and the second user B, namely the first correlation of the first user A and the second user B is the strong correlation condition, namely the two users of the first user A and the second user B are the same user.
S103, integrating first user information of a first user in a first scene and second user information of a second user in a second scene according to the first relevance by the electronic equipment to obtain third user information of the first user;
wherein the user information includes: the method comprises the following steps of user basic information, value information of a user, behavior information of the user, wherein the user basic information can be the name, the gender, the birthday, the contact way, certificate information and personal information of a first contact person associated with the user in a scene. Wherein the certificate information includes a certificate type and a certificate number. The contact way of the user can be common contact ways such as a mobile phone number, a landline number, an account number of instant messaging, a mailbox number and the like. The personal information of the first contact associated with the user under the scene comprises: name, job number, contact address of the first contact. The contact information of the first contact comprises any one of the following: the mobile phone number, the mailbox account number, the account number of instant messaging and the like of the first contact person. The first contact may be an associate with the user corresponding to the business in the scene.
Wherein the value information of the user may be value information determined by purchasing information of the user, historical consumption information, and historical purchase insurance financial product information.
The behavior information of the user comprises the time length and the time point of browsing insurance products and financial products on the application program APP within a preset time period, and the behavior information of the user also comprises historical purchase information of the user. The user historical purchase information may be: the type, amount, and time of purchase of the insurance financial product by the user is not overly limited. The application APP may be an APP related to a financial product, may be an APP related to an insurance product, and may be a payment type APP.
In a specific implementation, the electronic device integrates, according to the first relevance, first user information of the first user in a first scene and second user information of the second user in a second scene to obtain third user information of the first user, including but not limited to: the electronic equipment judges whether the first user and the second user are the same user or not according to the first relevance, and if yes, the electronic equipment integrates first user information of the first user in a first scene and second user information of the second user in a second scene to obtain third user information of the first user.
It should be noted that, the electronic device integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario, which includes but is not limited to: the electronic equipment compares the first user information with the second user information, and integrates information different from the first user information in the second user information into the first user information.
In a specific implementation, the electronic device integrates, according to the first relevance, first user information of the first user in a first scene and second user information of the second user in a second scene to obtain third user information of the first user, and the method further includes, but is not limited to: the electronic equipment judges whether the first user and the second user are the same user or not according to the first relevance, if not, the electronic equipment numbers the second user, and creates an Identity Document (ID) for the second user basic information of the second user, wherein the ID is the user number in the user basic information in the preset scene; and saving the second user information of the second user in the database. The preset scene is consistent with the preset scene description in the above embodiments, and redundant description is not repeated here.
S104, the electronic equipment determines the demand score of the first user for the first product according to the third user information;
in one possible example, before the electronic device determines the first user's demand score for the first product according to the third user information, the electronic device further includes: the electronic device establishes a demand scoring model of a first user demand for a first product.
In a specific implementation, the electronic device establishes a demand scoring model of a first user for a first product demand, including: the electronic equipment takes the user information of the first user as a predictive variable, converts the user information into a target variable, and constructs a demand scoring model, wherein the demand scoring model is a scoring model of the first user for the first product.
In one possible example, determining a first user demand score for the first product based on the third user information includes: and the electronic equipment determines the demand score of the first user on the first product according to the third user information of the first user by using the demand scoring model.
Wherein the demand scoring model comprises a logistic regression prediction model.
The logistic regression prediction model comprises the following components:Score(y＝1|X)＝β0+β1X1+β2X2+…++βnXnwherein Score (y ═ 1| X) represents the model Score of the customer conversion rate under the known label condition, β _ n is the label weight value of the third user information, XnThe third user information is a label, and the third user information comprises a plurality of labels.
It should be explained that, as shown in fig. 2, fig. 2 is a schematic flow chart illustrating a process of determining a demand score of a first user for a first product, where an electronic device determines a demand score of the first user for the first product according to third user information of the first user by using a demand scoring model, and the process includes, but is not limited to: and the electronic equipment calculates the demand score of the first user on the first product according to the third user information of the first user by using the logistic regression prediction model and the demand score calculation formula.
The demand score calculation formula of the first user is as follows:
Figure BDA0002841925060000091
wherein, Standard is the demand Score of the first user, Score is Score (y is 1-X), C is a constant, SPmin is the minimum conversion rate, SPmax is the maximum conversion rate, and Ip is a weighted value.
S105, the electronic equipment pushes the product information of the first product to the first user according to the demand score.
In one possible example, the electronic device pushes product information of a first product to a first user according to the demand score, and the method comprises the following steps: the electronic equipment determines the process of the first user according to the demand score of the first user; the electronic equipment pushes the product information of the first product to the first user according to the process of the first user.
It should be further explained that the electronic device determines the progress of the first user according to the demand score of the first user, including but not limited to: the electronic equipment divides the first user according to the demand score of the first user and determines the process of the first user.
The stage division rule of the process of the first user is as follows:
1. p3: the conversion rate corresponding to the demand score is more than 35 percent
2. P2: standardizing according to a demand score line with 35% conversion rate corresponding to the demand score, and taking the first 25% of a standardized score interval of 0-35% to enter P2
3. P1: and (4) standardizing according to a demand score line with 35% of conversion rate corresponding to the demand score, and taking 50% -75% of the standardized score interval 0-35% to enter P1.
Wherein, the stage P1 refers to the user being in the cognitive stage; stage P2, which means that the user is in operation; the stage P3 means that the user is in the accurate marketing stage.
It should be further explained that the electronic device pushes product information to the first user according to the progress of the first user, including but not limited to:
when the process of the first user is the stage P1, recommending related questionnaires, materials and information according to the label weight information in the user scoring model at the stage, and acquiring the demand information of the first user to perfect the understanding degree information of the first user;
when the process of the first user is the stage P2, in the stage, a demand tendency model of the user is constructed to obtain the general product tendency information of the user, and information of some savings products is recommended or partaking in the partnering activities of the savings products according to the product tendency information. For example, the major demand categories for individual risk products are only seven categories, namely educational (E06), non-health care (E02), savings (E05), elderly people (E00), critical illness protection (E04), medical protection (E03), and long-term care (E01). Seven classification models are constructed (e.g., using the lightGBM model), and the first user a is predicted to be interested in the savings type category in the individual insurance product. The user is interested in the deposit type products, and can recommend the information of some deposit type products or participate in the partnering activities of the deposit type products and the like;
when the first user's progress is stage P3, at this stage, a prediction is made of products that are of particular interest to the user. Firstly, a premium model of the user is constructed, and the premium model predicts a premium interval which can be borne by the user in the future. The premium segmentation comprises the following steps of constructing a multi-classification logistic regression model taking a premium segmentation interval as a target variable, predicting a most possible premium range of a user, assuming that the range is 4000- & ltSUB & gt 6000- & lt SUB & gt, then according to the demand tendency of the user in the stage P2, such as E05, a deposit type, recommending the user by inquiring products in the deposit type and the annual premium payment range of 4000- & ltSUB & gt 6000- & lt SUB & gt in a product system and combining a multi-product recommendation model (a result recommended by multiple logistic regression) of the user.
Wherein, the premium segmentation is divided according to the following results:
0-2000, 2000-4000, 4000-6000, 6000-8500, 8500.
It can be seen that, in the embodiment of the application, by acquiring the first user basic information of the first user in the first scene and the second user basic information of the second user in the second scene, the user basic information refers to the personal information of the user and the personal information of the first contact person associated with the user in the scene; identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information; according to the first relevance, integrating first user information of the first user in a first scene with second user information of the second user in a second scene to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information; determining the demand score of the first user for the first product according to the third user information; and pushing the product information of the first product to the first user according to the demand score. According to the embodiment of the application, the demand score of the first user on the first product is determined according to the integrated first user information, the product information is pushed to the first user according to the demand score, the first user information is perfected, the accuracy of the first user information is improved, and the accuracy and the efficiency of pushing the product information to the first user are improved.
The embodiments of the present application will be described in detail below with reference to a specific example.
Consistent with the embodiment shown in fig. 1, please refer to fig. 3, where fig. 3 is a schematic flowchart of a product information pushing method provided in an embodiment of the present application, and the method is applied to an electronic device, and the method includes:
s301, the electronic equipment acquires first user basic information of a first user in a first scene and second user basic information of a second user in a second scene;
the basic user information refers to personal information of a user and personal information of a first contact person associated with the user in a scene;
s302, the electronic equipment identifies the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information;
s303, the electronic equipment integrates first user information of the first user in a first scene and second user information of the second user in a second scene according to the first relevance to obtain third user information of the first user;
wherein the user information includes: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information;
s304, the electronic equipment takes the user information of the first user as a prediction variable, converts the user information into a target variable, and constructs a demand scoring model;
s305, the electronic equipment determines the demand score of the first user on the first product according to the third user information by using the demand scoring model;
s306, the electronic equipment determines the process of the first user according to the demand score of the first user;
s307, the electronic equipment pushes the product information of the first product to the first user according to the process of the first user.
It can be seen that, in the embodiment of the application, by acquiring the first user basic information of the first user in the first scene and the second user basic information of the second user in the second scene, the user basic information refers to the personal information of the user and the personal information of the first contact person associated with the user in the scene; identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information; according to the first relevance, integrating first user information of the first user in a first scene with second user information of the second user in a second scene to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information; determining the demand score of the first user for the first product according to the third user information; and pushing the product information of the first product to the first user according to the demand score. According to the embodiment of the application, the demand score of the first user on the first product is determined according to the integrated first user information, the product information is pushed to the first user according to the demand score, the first user information is perfected, the accuracy of the first user information is improved, the accuracy of pushing proper product information to the first user is improved, and the efficiency of pushing the product information to the first user is improved.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device 400 according to an embodiment of the present application, and as shown in the drawing, the electronic device 400 includes an application processor 410, a memory 420, a communication interface 430, and one or more programs 421, where the one or more programs 421 are stored in the memory 420 and configured to be executed by the application processor 410, and the one or more programs 421 include instructions for performing the following steps:
acquiring first user basic information of a first user in a first scene and second user basic information of a second user in a second scene, wherein the user basic information refers to personal information of the user and personal information of a first contact person associated with the user in the scene;
identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information;
integrating first user information of the first user in a first scene and second user information of the second user in a second scene according to the first relevance to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information;
determining the demand score of the first user for the first product according to the third user information;
and pushing the product information of the first product to the first user according to the demand score.
It can be seen that, in the embodiment of the application, by acquiring the first user basic information of the first user in the first scene and the second user basic information of the second user in the second scene, the user basic information refers to the personal information of the user and the personal information of the first contact person associated with the user in the scene; identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information; according to the first relevance, integrating first user information of the first user in a first scene with second user information of the second user in a second scene to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information; determining the demand score of the first user for the first product according to the third user information; and pushing the product information of the first product to the first user according to the demand score. According to the embodiment of the application, the demand score of the first user on the first product is determined according to the integrated first user information, the product information is pushed to the first user according to the demand score, the first user information is perfected, the accuracy of the first user information is improved, and the accuracy and the efficiency of pushing the product information to the first user are improved.
In one possible embodiment, said one or more programs 421 further comprise instructions for, prior to said determining a first user demand score for a first product based on said third user information, performing the steps of:
and establishing a demand scoring model of the first user for the first product demand.
In one possible embodiment, said modeling the demand score for the first product demand by the first user, said one or more programs 421 comprise instructions for performing the steps of: and converting user information of a first user into a target variable by taking the user information of the first user as a predictive variable, and constructing the demand scoring model, wherein the demand scoring model is a scoring model of the first user for the first product.
In one possible embodiment, said determining a demand score for a first product by said first user based on said third user information, said one or more programs 421 comprise instructions for performing the steps of: and determining the demand score of the first user on the first product according to the third user information of the first user by using a demand scoring model.
In one possible embodiment, the demand scoring model comprises a logistic regression prediction model.
In one possible embodiment, the pushing product information of the first product to the first user according to the demand score includes the one or more programs 421 configured to perform the following steps: determining the process of the first user according to the demand score of the first user; and pushing the product information of the first product to the first user according to the process of the first user.
In one possible embodiment, the logistic regression prediction model is: score (y ═ 1| X) ═ β0+β1X1+β2X2+…++βnXnWhere Score (y ═ 1| X) represents the model Score for customer conversion under known label conditions, βnA label weight value, X, for the third user informationnA label for third user information.
The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the above-mentioned functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Fig. 5 is a block diagram of functional units of a product information pushing apparatus 500 according to an embodiment of the present application. The product information pushing apparatus 500 includes:
an obtaining unit 501, configured to obtain first user basic information of a first user in a first scene and second user basic information of a second user in a second scene;
an identifying unit 502, configured to identify the first user basic information and the second user basic information to obtain a first association between the first user basic information and the second user basic information;
an integrating unit 503, configured to integrate, according to the first relevance, first user information of the first user in a first scene and second user information of the second user in a second scene to obtain third user information of the first user;
a determining unit 504, configured to determine, according to the third user information, a demand score of the first user for the first product;
and a pushing unit 505, configured to push product information of the first product to the first user according to the demand score.
The product information pushing apparatus 500 may further include a storage unit 506 for storing program codes and data of the electronic device. The storage unit 506 may be a memory.
It can be seen that, in the embodiment of the application, by acquiring the first user basic information of the first user in the first scene and the second user basic information of the second user in the second scene, the user basic information refers to the personal information of the user and the personal information of the first contact person associated with the user in the scene; identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information; according to the first relevance, integrating first user information of the first user in a first scene with second user information of the second user in a second scene to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information; determining the demand score of the first user for the first product according to the third user information; and pushing the product information of the first product to the first user according to the demand score. According to the embodiment of the application, the demand score of the first user on the first product is determined according to the integrated first user information, the product information is pushed to the first user according to the demand score, the first user information is perfected, the accuracy of the first user information is improved, and the accuracy and the efficiency of pushing the product information to the first user are improved.
In a possible embodiment, before determining the first user's demand score for the first product according to the third user information, the determining unit 504 is further specifically configured to: and establishing a demand scoring model of the first user for the first product demand.
In one possible embodiment, in establishing a demand scoring model of the first user for the first product demand, the determining unit 504 is further specifically configured to: and converting the user information of the first user into a target variable by taking the user information of the first user as a prediction variable, and constructing a demand scoring model, wherein the demand scoring model is a scoring model of the first user for the first product.
In a possible embodiment, in determining the demand score of the first user for the first product according to the third user information, the determining unit 504 is further specifically configured to: and determining the demand score of the first user on the first product according to the third user information of the first user by using the demand scoring model.
In one possible embodiment, the demand scoring model includes a logistic regression prediction model.
In a possible embodiment, in terms of pushing the product information of the first product to the first user according to the demand score, the pushing unit 505 is specifically configured to: determining the process of the first user according to the demand score of the first user; and pushing the product information of the first product to the first user according to the process of the first user.
In one possible embodiment, the logistic regression prediction model is: score (y ═ 1| X) ═ β0+β1Xi+β2X2+…++βnXnWhere Score (y ═ 1| X) represents the model Score for customer conversion under known label conditions, βnA label weight value, X, for the third user informationnA label for third user information.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (10)

1. A product information pushing method is applied to an electronic device, and comprises the following steps:
acquiring first user basic information of a first user in a first scene and second user basic information of a second user in a second scene, wherein the user basic information refers to personal information of the user and personal information of a first contact person associated with the user in the scene;
identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information;
integrating first user information of the first user in a first scene and second user information of the second user in a second scene according to the first relevance to obtain third user information of the first user, wherein the user information comprises: the method comprises the following steps of (1) user basic information, user value information, user behavior information and user historical purchase information;
determining the demand score of the first user for the first product according to the third user information;
and pushing the product information of the first product to the first user according to the demand score.
2. The method of claim 1, wherein prior to determining the first user's demand score for the first product based on the third user information, further comprising:
and establishing a demand scoring model of the first user for the first product demand.
3. The method of claim 2, wherein said modeling a demand score for a first product demand by said first user comprises:
and converting user information of a first user into a target variable by taking the user information of the first user as a predictive variable, and constructing the demand scoring model, wherein the demand scoring model is a scoring model of the first user for the first product.
4. The method of claim 1, wherein said determining a first user demand score for a first product from said third user information comprises:
and determining the demand score of the first user on the first product according to the third user information of the first user by using a demand scoring model.
5. The method according to any one of claims 2 to 4,
the demand scoring model includes a logistic regression prediction model.
6. The method of claim 5, wherein the logistic regression prediction model is: score (y ═ 1| X) ═ β0+β1X1+β2X2+…++βnXn，
Where Score (y ═ 1| X) represents the model Score for customer conversion under known label conditions, βnA label weight value, X, for the third user informationnA label for third user information.
7. The method of claim 1, wherein pushing product information of the first product to the first user according to the demand score comprises:
determining the process of the first user according to the demand score of the first user;
and pushing the product information of the first product to the first user according to the process of the first user.
8. A product information pushing apparatus, characterized in that the apparatus comprises:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring first user basic information of a first user in a first scene and second user basic information of a second user in a second scene;
the identification unit is used for identifying the first user basic information and the second user basic information to obtain a first relevance between the first user basic information and the second user basic information;
the integration unit is used for integrating first user information of the first user in a first scene and second user information of the second user in a second scene according to the first relevance to obtain third user information of the first user;
the determining unit is used for determining the demand score of the first user for the first product according to the third user information;
and the pushing unit is used for pushing the product information of the first product to the first user according to the demand score.
9. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that it stores a computer program for electronic data exchange, wherein the computer program causes a computer to perform the method according to any one of claims 1-7.
CN202011499114.7A 2020-12-17 2020-12-17 Product information pushing method and related product Pending CN112561651A (en)

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CN110610378A (en) * 2019-08-14 2019-12-24 深圳壹账通智能科技有限公司 Product demand analysis method and device, computer equipment and storage medium
CN111652282A (en) * 2020-04-30 2020-09-11 中国平安财产保险股份有限公司 Big data based user preference analysis method and device and electronic equipment
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Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110019940A (en) * 2017-08-03 2019-07-16 Tcl集团股份有限公司 A kind of video display method for pushing and device
CN110610378A (en) * 2019-08-14 2019-12-24 深圳壹账通智能科技有限公司 Product demand analysis method and device, computer equipment and storage medium
CN111652282A (en) * 2020-04-30 2020-09-11 中国平安财产保险股份有限公司 Big data based user preference analysis method and device and electronic equipment
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